A Machine Learning Approach for Game Bot Detection Through Behavioural Features

  • Mario Luca Bernardi
  • Marta CimitileEmail author
  • Fabio Martinelli
  • Francesco Mercaldo
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 868)


In the last years, online games market has been interested by a sudden growth due to the birth of new gaming infrastructures that offer more effective and innovative services and products. Simultaneously to the diffusion of on line games, there was an increasing use of game bots to automatically perform malicious tasks. Game bots users aim to obtain some rewards by automating the most tedious and prolonged activities arousing the disappointment of the game community. Therefore, the detection and the expulsion of game bots from the game environment, become critical issues for the game’s developers that want to ensure the satisfaction of all the players. This paper describes an approach for the game bot detection in the online role player games consisting to distinguish between game bots and human behavior and based on the adoption of supervised and unsupervised machine learning techniques. These techniques are used to discriminate between users and game bots basing on some user behavioral features. The approach is applied to a real-world dataset of a popular role player game and the obtained results are encouraging.


Game bot Machine learning Cluster analysis Game bot detection Security Testing 



This work has been partially supported by H2020 EU-funded projects NeCS and C3ISP and EIT-Digital Project HII.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mario Luca Bernardi
    • 1
  • Marta Cimitile
    • 2
    Email author
  • Fabio Martinelli
    • 3
  • Francesco Mercaldo
    • 3
  1. 1.Giustino Fortunato UniversityBeneventoItaly
  2. 2.Unitelma SapienzaRomaItaly
  3. 3.Institute for Informatics and TelematicsNational Research Council of Italy (CNR)PisaItaly

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